Forchheim, Germany

Barbara Brehm


Average Co-Inventor Count = 12.0

ph-index = 1


Company Filing History:


Years Active: 2024

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1 patent (USPTO):Explore Patents

Title: Barbara Brehm: Innovator in Medical Imaging Technology

Introduction

Barbara Brehm is a prominent inventor based in Forchheim, Germany. She has made significant contributions to the field of medical imaging, particularly in the area of machine learning applications for healthcare. Her innovative work focuses on enhancing the accuracy and reliability of clinical decision-making through advanced technology.

Latest Patents

Barbara Brehm holds a patent for her invention titled "Machine learning for automatic detection of intracranial hemorrhages with uncertainty measures from medical images." This patent describes systems and methods for performing a medical imaging analysis task aimed at making clinical decisions. The process involves receiving one or more input medical images of a patient and utilizing a machine learning-based network to perform the analysis. The network generates a probability score associated with the analysis task, and an uncertainty measure related to this score is determined. Ultimately, a clinical decision is made based on both the probability score and the uncertainty measure. This innovative approach has the potential to significantly improve patient outcomes in medical settings.

Career Highlights

Barbara Brehm is currently employed at Siemens Healthineers AG, where she continues to develop cutting-edge technologies in medical imaging. Her work is instrumental in advancing the capabilities of healthcare professionals to make informed decisions based on accurate data analysis.

Collaborations

Barbara collaborates with talented colleagues, including Eli Gibson and Bogdan Georgescu, who contribute to her projects and enhance the overall impact of their work in the field of medical imaging.

Conclusion

Barbara Brehm's contributions to medical imaging through her innovative patent demonstrate her commitment to improving healthcare technology. Her work not only showcases her expertise but also highlights the importance of machine learning in clinical decision-making.

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